OpenSubdiv: Re-work C-API integration

Main goal is to make API simpler to follow (at least ion terms what
is defined/declared where, as opposite of handful big headers which
includes all the declarations), and also avoid a big set of long and
obscure functions.

Now C-API files are split into smaller ones, following OpenSubdiv
behavior more closely, and also function pointers in structures
used a lot more, which shortens functions names,

UV integration part in GL Mesh is mainly stripped away, it needs
to be done differently. On a related topic, UV coordinates API in
converter needs to be removed as well, we do not need coordinates,
only island connectivity information there.

Additional changes:

- Varying interpolation in evaluator API are temporarily disabled,
  need to extend API somewhere (probably, evaluator's API) to inform
  layout information of vertex data (whether it contains varying
  data, width, stride and such).

- Evaluator now can interpolate face-varying data.
  Only works for adaptive refiner, since some issues in OpenSubdiv
  itself.

Planned changes:

- Remove uv coordinates from TopologyConverter.
- Support evaluation of patches (as opposite to individual coordinates
  as it happens currently).
- Support more flexible layout of varying and face-varying data.
  It is stupid to assume varying is 3 floats and face-varying 2 floats.
- Support of second order derivatives.
- Everything else what i'm missing in this list.

1 files changed, 226 insertions, 0 deletions

diff --git a/intern/opensubdiv/internal/opensubdiv_device_context_cuda.cc b/intern/opensubdiv/internal/opensubdiv_device_context_cuda.cc
new file mode 100644
index 00000000000..875f503b9ab
--- /dev/null
+++ b/intern/opensubdiv/internal/opensubdiv_device_context_cuda.cc
@@ -0,0 +1,226 @@
+// Adopted from OpenSubdiv with the following license:
+//
+//   Copyright 2015 Pixar
+//
+//   Licensed under the Apache License, Version 2.0 (the "Apache License")
+//   with the following modification; you may not use this file except in
+//   compliance with the Apache License and the following modification to it:
+//   Section 6. Trademarks. is deleted and replaced with:
+//
+//   6. Trademarks. This License does not grant permission to use the trade
+//      names, trademarks, service marks, or product names of the Licensor
+//      and its affiliates, except as required to comply with Section 4(c) of
+//      the License and to reproduce the content of the NOTICE file.
+//
+//   You may obtain a copy of the Apache License at
+//
+//       http://www.apache.org/licenses/LICENSE-2.0
+//
+//   Unless required by applicable law or agreed to in writing, software
+//   distributed under the Apache License with the above modification is
+//   distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+//   KIND, either express or implied. See the Apache License for the specific
+//   language governing permissions and limitations under the Apache License.
+
+#ifdef OPENSUBDIV_HAS_CUDA
+
+#ifdef _MSC_VER
+#  include <iso646.h>
+#endif
+
+#include "opensubdiv_device_context_cuda.h"
+
+#if defined(_WIN32)
+#  include <windows.h>
+#elif defined(__APPLE__)
+#  include <OpenGL/OpenGL.h>
+#else
+#  include <GL/glx.h>
+#  include <X11/Xlib.h>
+#endif
+
+#include <cuda.h>
+#include <cuda_gl_interop.h>
+#include <cuda_runtime_api.h>
+#include <algorithm>
+#include <cstdio>
+
+#define message(fmt, ...)
+// #define message(fmt, ...)  fprintf(stderr, fmt, __VA_ARGS__)
+#define error(fmt, ...) fprintf(stderr, fmt, __VA_ARGS__)
+
+namespace {
+
+int getCudaDeviceForCurrentGLContext() {
+  // Find and use the CUDA device for the current GL context
+  unsigned int interop_device_count = 0;
+  int interopDevices[1];
+  cudaError_t status = cudaGLGetDevices(&interop_device_count,
+                                        interopDevices,
+                                        1,
+                                        cudaGLDeviceListCurrentFrame);
+  if (status == cudaErrorNoDevice || interop_device_count != 1) {
+    message("CUDA no interop devices found.\n");
+    return 0;
+  }
+  int device = interopDevices[0];
+#if defined(_WIN32)
+  return device;
+#elif defined(__APPLE__)
+  return device;
+#else  // X11
+  Display* display = glXGetCurrentDisplay();
+  int screen = DefaultScreen(display);
+  if (device != screen) {
+    error("The CUDA interop device (%d) does not match "
+          "the screen used by the current GL context (%d), "
+          "which may cause slow performance on systems "
+          "with multiple GPU devices.",
+          device, screen);
+  }
+  message("CUDA init using device for current GL context: %d\n", device);
+  return device;
+#endif
+}
+
+// Beginning of GPU Architecture definitions.
+int convertSMVer2Cores_local(int major, int minor) {
+  // Defines for GPU Architecture types (using the SM version to determine
+  // the # of cores per SM
+  typedef struct {
+    int SM;  // 0xMm (hexidecimal notation),
+             // M = SM Major version,
+             // and m = SM minor version
+    int Cores;
+  } sSMtoCores;
+
+  sSMtoCores nGpuArchCoresPerSM[] = {
+      {0x10, 8},    // Tesla Generation (SM 1.0) G80 class.
+      {0x11, 8},    // Tesla Generation (SM 1.1) G8x class.
+      {0x12, 8},    // Tesla Generation (SM 1.2) G9x class.
+      {0x13, 8},    // Tesla Generation (SM 1.3) GT200 class.
+      {0x20, 32},   // Fermi Generation (SM 2.0) GF100 class.
+      {0x21, 48},   // Fermi Generation (SM 2.1) GF10x class.
+      {0x30, 192},  // Fermi Generation (SM 3.0) GK10x class.
+      {-1, -1}};
+  int index = 0;
+  while (nGpuArchCoresPerSM[index].SM != -1) {
+    if (nGpuArchCoresPerSM[index].SM == ((major << 4) + minor)) {
+      return nGpuArchCoresPerSM[index].Cores;
+    }
+    index++;
+  }
+  printf("MapSMtoCores undefined SMversion %d.%d!\n", major, minor);
+  return -1;
+}
+
+// This function returns the best GPU (with maximum GFLOPS).
+int cutGetMaxGflopsDeviceId() {
+  int current_device = 0, sm_per_multiproc = 0;
+  int max_compute_perf = 0, max_perf_device = -1;
+  int device_count = 0, best_SM_arch = 0;
+  int compat_major, compat_minor;
+  cuDeviceGetCount(&device_count);
+  // Find the best major SM Architecture GPU device.
+  while (current_device < device_count) {
+    cuDeviceComputeCapability(&compat_major, &compat_minor, current_device);
+    if (compat_major > 0 && compat_major < 9999) {
+      best_SM_arch = std::max(best_SM_arch, compat_major);
+    }
+    current_device++;
+  }
+  // Find the best CUDA capable GPU device.
+  current_device = 0;
+  while (current_device < device_count) {
+    cuDeviceComputeCapability(&compat_major, &compat_minor, current_device);
+    if (compat_major == 9999 && compat_minor == 9999) {
+      sm_per_multiproc = 1;
+    } else {
+      sm_per_multiproc = convertSMVer2Cores_local(compat_major, compat_minor);
+    }
+    int multi_processor_count;
+    cuDeviceGetAttribute(&multi_processor_count,
+                         CU_DEVICE_ATTRIBUTE_MULTIPROCESSOR_COUNT,
+                         current_device);
+    int clock_rate;
+    cuDeviceGetAttribute(&clock_rate, CU_DEVICE_ATTRIBUTE_CLOCK_RATE,
+                         current_device);
+    int compute_perf = multi_processor_count * sm_per_multiproc * clock_rate;
+    if (compute_perf > max_compute_perf) {
+      /* If we find GPU with SM major > 2, search only these */
+      if (best_SM_arch > 2) {
+        /* If our device==dest_SM_arch, choose this, or else pass. */
+        if (compat_major == best_SM_arch) {
+          max_compute_perf = compute_perf;
+          max_perf_device = current_device;
+        }
+      } else {
+        max_compute_perf = compute_perf;
+        max_perf_device = current_device;
+      }
+    }
+    ++current_device;
+  }
+  return max_perf_device;
+}
+
+}  // namespace
+
+bool CudaDeviceContext::HAS_CUDA_VERSION_4_0() {
+#ifdef OPENSUBDIV_HAS_CUDA
+  static bool cuda_initialized = false;
+  static bool cuda_load_success = true;
+  if (!cuda_initialized) {
+    cuda_initialized = true;
+
+#ifdef OPENSUBDIV_HAS_CUEW
+    cuda_load_success = cuewInit(CUEW_INIT_CUDA) == CUEW_SUCCESS;
+    if (!cuda_load_success) {
+      fprintf(stderr, "Loading CUDA failed.\n");
+    }
+#endif
+    // Need to initialize CUDA here so getting device
+    // with the maximum FPLOS works fine.
+    if (cuInit(0) == CUDA_SUCCESS) {
+      // This is to deal with cases like NVidia Optimus,
+      // when there might be CUDA library installed but
+      // NVidia card is not being active.
+      if (cutGetMaxGflopsDeviceId() < 0) {
+        cuda_load_success = false;
+      }
+    } else {
+      cuda_load_success = false;
+    }
+  }
+  return cuda_load_success;
+#else
+  return false;
+#endif
+}
+
+CudaDeviceContext::CudaDeviceContext()
+    : initialized_(false) {
+}
+
+CudaDeviceContext::~CudaDeviceContext() {
+  cudaDeviceReset();
+}
+
+bool CudaDeviceContext::Initialize() {
+  // See if any cuda device is available.
+  int device_count = 0;
+  cudaGetDeviceCount(&device_count);
+  message("CUDA device count: %d\n", device_count);
+  if (device_count <= 0) {
+    return false;
+  }
+  cudaGLSetGLDevice(getCudaDeviceForCurrentGLContext());
+  initialized_ = true;
+  return true;
+}
+
+bool CudaDeviceContext::IsInitialized() const {
+  return initialized_;
+}
+
+#endif  // OPENSUBDIV_HAS_CUDA